Intelligent chemical engineering site construction safety and quality detection method and system based on big data

Abstract

The invention relates to the technical field of intelligent chemical engineering, and discloses an intelligent chemical engineering construction safety and quality detection method based on big data, and the method comprises the following steps: 1, installing a monitor and a sensor; step 2, intelligent analysis; step 3, predictive maintenance; step 4, risk assessment; step 5, quality control; step 6, safety management; 7, accident prevention; 8, remote real-time management is carried out; step 9, decision support; step 10, intelligent reporting; and step 11, displaying an interface. According to the intelligent chemical engineering site construction safety and quality detection method and system based on big data, through real-time monitoring and risk assessment, the intelligent chemical engineering site system can improve the safety management level of a construction site and reduce accidents, and the system can predict potential safety risks and take measures to avoid the potential safety risks by utilizing predictive maintenance and accident prevention technologies; and by using big data and an intelligent optimization algorithm, the resource allocation and the construction process are optimized, and the construction efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart chemical sites, and specifically to a construction safety and quality detection method and system for smart chemical sites based on big data. Background Art

[0002] A smart construction site is a new construction management model that uses modern information technology, especially the Internet of Things, big data, cloud computing, artificial intelligence and other technologies, to achieve comprehensive perception, real-time monitoring, intelligent analysis and scientific decision-making of construction sites. The implementation of a smart construction site requires comprehensive consideration of technology, management, personnel and other factors. Through continuous technological innovation and optimization, the level of intelligence in construction can be improved to achieve efficient, safe and sustainable development of the construction process.

[0003] However, the current smart construction sites are inadequate in construction safety management, quality inspection and control are not strict enough, and accident prevention capabilities are weak, which will cause certain resource waste and low efficiency. In addition, there are insufficient emergency response and disposal capabilities, imprecise labor management, and lagging equipment maintenance and fault diagnosis, which lead to long equipment failure downtime and can no longer meet the current needs of smart construction sites. Summary of the invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a smart construction site construction safety and quality detection method and system based on big data, which has the advantages of significantly improving the management level of the construction site, ensuring construction safety and project quality, and improving construction efficiency and resource utilization.

[0005] In order to achieve the above-mentioned purpose of significantly improving the management level of the construction site, ensuring construction safety and project quality, and improving construction efficiency and resource utilization, the present invention provides the following technical solution: a smart construction site construction safety and quality detection method based on big data, the method comprising the following steps: Step 1: Install monitoring and sensors. Place multiple sensors and cameras at the construction site to monitor the environmental conditions, equipment status and worker activities at the construction site in real time. Step 2: Intelligent analysis, which uses machine learning algorithms to analyze the collected data to identify potential safety risks and quality issues; Step 3: Predictive maintenance, using big data to predict equipment failures and maintenance needs, reduce unexpected downtime, and improve construction efficiency; Step 4: Risk assessment: conduct real-time assessment of the risks of high-altitude operations or electrical safety risk factors at the construction site, issue early warnings in a timely manner, and take preventive measures; Step 5: Quality control, using image recognition and data analysis technology through the quality inspection system to automatically detect the concrete strength and steel layout construction quality to ensure compliance with standards; Step 6: Safety management: Worker identity verification through fingerprint or facial recognition technology to ensure that only authorized personnel enter the construction site area, and then use smart wearable devices to ensure that workers wear and use safety equipment correctly; Step 7: Accident prevention, by analyzing workers’ dangerous behaviors and on-site safety conditions, predicting possible accidents and taking measures to avoid them; Step 8: Remote real-time management: project managers and safety managers can remotely view the surveillance video of the camera through the cloud platform and manage the construction site in real time; Step 9: Decision support, providing big data-driven decision support to help management develop more effective construction plans and safety strategies; Step 10: Intelligent reporting: the system automatically generates construction progress and safety and quality reports for easy review and recording; Step 11: Interface display: the text and pictures implemented by the above steps are displayed through a mobile APP or a display screen, so that all users can quickly access and view the required information.

[0006] Preferably, it also includes using virtual reality and augmented reality technology to conduct safety education and skills training for workers, simulating potential dangerous situations and emergency responses, allowing workers to practice different ways of dealing with different dangerous situations, and allowing multiple users to participate in training at the same time for team collaboration and communication.

[0007] Preferably, the environmental conditions in step 1 collect temperature, humidity, noise, vibration and air quality data, as well as construction progress and quality indicators through various sensors. The equipment status specifically refers to the vibration, pressure and current of the equipment to facilitate the later prediction of equipment failure. The worker activities specifically use video analysis software to detect whether the workers are working in a dangerous area.

[0008] Preferably, step 5 also includes using 3D laser scanning technology to obtain accurate three-dimensional data of the construction area, comparing it with the design model, detecting construction deviations, integrating and comparing the design data with the actual construction situation through BIM technology, realizing visualization and quality control of the construction process, and using RFID tags to track building materials and components to ensure the correctness and traceability of material use.

[0009] Preferably, the various hardware devices, software applications and data platforms in each step are integrated into a unified system to achieve data sharing and functional collaboration for better management.

[0010] A smart construction site safety and quality inspection system based on big data, including video surveillance module, sensor network module, behavior recognition module, worker safety module, geographic information module, Internet of Things platform, predictive analysis module, accident reporting and tracking module, mobile application and alarm module, risk assessment module, cloud platform and emergency response module; The video monitoring module monitors the construction site in real time through cameras installed at key locations; The sensor network module monitors the status of construction equipment by deploying environmental sensors on the construction site to monitor environmental parameters and installing equipment sensors on the construction site equipment; The behavior recognition module is used to train the model to identify improper operations or specific illegal behaviors of workers; The worker safety module is used for health monitoring components and location tracking components worn on workers; The geographic information module is used to analyze the spatial distribution of workers and equipment using GIS software and optimize the construction layout; The IoT platform is used to integrate data from various devices and sensors into the IoT platform, and then use the analysis tools and other modules of the IoT platform itself to make data-driven decisions; The predictive analysis module predicts potential safety risks by analyzing historical data and real-time data, and identifies trends in safety and quality issues, taking measures in advance to perform trend analysis; The accident reporting and tracking module allows workers and managers to report accidents through mobile devices or web pages, and the system automatically records and analyzes accident reports to find out the specific causes; The mobile application and alarm module allows managers and workers to communicate in real time through the mobile application. When a dangerous situation is detected, the system can send an emergency alarm through the mobile application; The risk assessment module uses a mobile device or web page to conduct daily safety checks and also uses software tools to assess the risk level of specific operations; The cloud platform is used to store all monitoring and analysis data in the cloud, ensuring data security and accessibility, and enabling managers to remotely access the monitoring system through any device; The emergency response module formulates detailed emergency plans for different situations and integrates them into the system. When an accident occurs, the system automatically activates the corresponding emergency plan to guide on-site personnel to handle the emergency.

[0011] Preferably, the behavior recognition module also includes using video analysis software to detect whether the worker is wearing safety equipment or working in a dangerous area.

[0012] Preferably, the worker safety module also includes a smart safety helmet with built-in sensors to detect impacts, record accident data, and has environmental monitoring capabilities for both impact detection and monitoring of the worker's surrounding environmental conditions.

[0013] Preferably, it also includes a personnel entry and exit monitoring module, which uses near field communication technology to set NFC tags at the entrance and key areas of the construction site, and workers sign in and locate through NFC devices.

[0014] Preferably, it also includes VR and AR training modules, devices for immersive experience or covering real vision through head-mounted displays and smart glasses, and software for developing and running VR and AR applications that simulate construction environments and safety training scenarios. It uses 3D modeling software to create three-dimensional models of construction sites, equipment and processes, conduct safety education, skills training, construction simulation and on-site navigation, improve workers' safety awareness and operational skills, and optimize construction processes and project management.

[0015] Compared with the prior art, the present invention provides a smart construction site safety and quality detection method and system based on big data, which has the following beneficial effects: 1. The construction safety and quality detection method and system of the smart construction site based on big data can improve the safety management level of the construction site and reduce accidents through real-time monitoring and risk assessment. The system can predict potential safety risks and take measures to avoid them by using predictive maintenance and accident prevention technology. Through intelligent analysis and quality control technology, the system can automatically detect the construction quality to ensure that the project quality meets the standards. With integrated environmental monitoring sensors, the system can monitor the environmental conditions of the construction site in real time to ensure the safety of the construction environment. Using big data and intelligent optimization algorithms, the system can optimize resource allocation and construction processes to improve construction efficiency.

[0016] 2. The intelligent construction site construction safety and quality inspection method and system based on big data integrates various hardware devices and software applications to achieve data sharing and functional collaboration, solves the problem of information islands, provides data-driven decision support, helps management formulate more effective construction plans and safety strategies, and uses virtual reality and augmented reality technologies to conduct safety education and skills training for workers to improve training effectiveness. Through intelligent reporting and regulatory compliance functions, the system can ensure that the construction process complies with all relevant regulations and industry standards, establish an emergency response system and emergency plan, and improve the emergency response and handling capabilities of the construction site. Using biometric technology and smart wearable devices, the system can accurately manage the labor force and ensure the safety of workers. Predictive maintenance technology can detect equipment failures in advance and reduce unexpected downtime. Real-time monitoring and data analysis technology can provide accurate construction progress information to help projects be completed on time, so as to significantly improve the management level of the construction site, ensure construction safety and project quality, and at the same time improve construction efficiency and resource utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of the smart construction site construction safety and quality detection method based on big data proposed by the present invention; Figure 2 This is a schematic diagram of the smart construction site construction safety and quality inspection system based on big data proposed in the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 , a smart construction site construction safety and quality detection method based on big data, the method includes the following steps: Step 1: Install monitoring and sensors. Multiple sensors and cameras are placed in the construction site to monitor the environmental conditions, equipment status and worker activities of the construction site in real time. The environmental conditions in step 1 collect temperature, humidity, noise, vibration and air quality data, as well as construction progress and quality indicators through various sensors. The equipment status specifically refers to the vibration, pressure and current of the equipment to facilitate the prediction of equipment failure in the later stage. The worker activities specifically use video analysis software to detect whether workers are working in dangerous areas; Step 2: Intelligent analysis, which uses machine learning algorithms to analyze the collected data to identify potential safety risks and quality issues; Step 3: Predictive maintenance, using big data to predict equipment failures and maintenance needs, reduce unexpected downtime, and improve construction efficiency; Step 4: Risk assessment: conduct real-time assessment of the risks of high-altitude operations or electrical safety risk factors at the construction site, issue early warnings in a timely manner, and take preventive measures; Step 5: Quality control. The quality inspection system uses image recognition and data analysis technology to automatically detect the strength of concrete and the quality of steel bar layout construction to ensure compliance with standards. Step 5 also includes the use of 3D laser scanning technology to obtain accurate three-dimensional data of the construction area, compare it with the design model, and detect construction deviations. Through BIM technology, the design data is integrated and compared with the actual construction situation to achieve visualization and quality control of the construction process. RFID tags are used to track building materials and components to ensure the correctness and traceability of material use. Step 6: Safety management: Worker identity verification through fingerprint or facial recognition technology to ensure that only authorized personnel enter the construction site area, and then use smart wearable devices to ensure that workers wear and use safety equipment correctly; Step 7: Accident prevention, by analyzing workers’ dangerous behaviors and on-site safety conditions, predicting possible accidents and taking measures to avoid them; Step 8: Remote real-time management: project managers and safety managers can remotely view the surveillance video of the camera through the cloud platform and manage the construction site in real time; Step 9: Decision support, providing big data-driven decision support to help management develop more effective construction plans and safety strategies; Step 10: Intelligent reporting: the system automatically generates construction progress and safety and quality reports for easy review and recording; Step 11: Interface display, displaying the text and pictures implemented by the above steps through a mobile APP or display screen, so that all users can quickly access and view the required information; The method also includes using virtual reality and augmented reality technology to conduct safety education and skills training for workers, simulating potential dangerous situations and emergency responses, allowing workers to practice different ways of dealing with different dangerous situations, and allowing multiple users to participate in training at the same time for team collaboration and communication. The method also includes integrating various hardware devices, software applications and data platforms in each step into a unified system to achieve data sharing and functional collaboration for better management; See also Figure 2, a smart construction site construction safety and quality inspection system based on big data, including video monitoring module, sensor network module, behavior recognition module, worker safety module, geographic information module, Internet of Things platform, predictive analysis module, accident reporting and tracking module, mobile application and alarm module, risk assessment module, cloud platform and emergency response module, and also includes personnel entry and exit monitoring module. Through near-field communication technology, NFC tags are set at the entrance and key areas of the construction site, and workers sign in and locate through NFC devices. It also includes VR and AR training modules, which use head-mounted displays and smart glasses for immersive experience or devices covering real vision. At the same time, software for simulating construction environments, safety training scenarios VR and AR applications is developed and run. 3D modeling software is used to create three-dimensional models of construction sites, equipment and processes, and safety education, skills training, construction simulation and on-site navigation are carried out to improve workers' safety awareness and operating skills, and optimize construction processes and project management; Video surveillance module, which monitors the construction site in real time through cameras installed in key locations; The sensor network module monitors the status of construction equipment by deploying environmental sensors on site to monitor environmental parameters and installing equipment sensors on site equipment; The behavior recognition module is used to train the model to identify workers’ improper operations or specific violations. The behavior recognition module also includes the use of video analysis software to detect whether workers are wearing safety equipment or working in dangerous areas; Worker safety module, which includes health monitoring components and location tracking components that are worn on workers. The worker safety module also includes smart hard hats with built-in sensors to detect impacts and record accident data, as well as environmental monitoring functions to detect impacts and monitor the environmental conditions around the worker; Geographic information module, which uses GIS software to analyze the spatial distribution of workers and equipment and optimize construction layout; IoT platform, which is used to integrate data from various devices and sensors into the IoT platform, and then use the analysis tools and other modules of the IoT platform itself to make data-driven decisions; The predictive analysis module predicts potential safety risks by analyzing historical data and real-time data, and identifies trends in safety and quality issues to take measures in advance to perform trend analysis; An accident reporting and tracking module, where workers and managers can report accidents through mobile devices or web pages, while the system automatically records and analyzes accident reports to find out the specific causes; Mobile application and alarm module, managers and workers communicate in real time through mobile applications, and when dangerous situations are detected, the system can send emergency alarms through mobile applications; Risk Assessment Module, which uses a mobile device or web page to conduct daily safety checks and also uses software tools to assess the risk level of specific operations; Cloud platform, which is used to store all monitoring and analysis data in the cloud, ensuring data security and accessibility, and enabling managers to remotely access the monitoring system through any device; The emergency response module develops detailed emergency plans for different situations and integrates them into the system. When an accident occurs, the system automatically activates the corresponding emergency plan and guides on-site personnel to handle the emergency.

[0020] In summary, the construction safety and quality detection method and system of the smart construction site based on big data can improve the safety management level of the construction site and reduce the occurrence of accidents through real-time monitoring and risk assessment when in use. The system can predict potential safety risks and take measures to avoid them by using predictive maintenance and accident prevention technology. Through intelligent analysis and quality control technology, the system can automatically detect the construction quality to ensure that the project quality meets the standards. With integrated environmental monitoring sensors, the system can monitor the environmental conditions of the construction site in real time to ensure the safety of the construction environment. Using big data and intelligent optimization algorithms, the system can optimize resource allocation and construction processes to improve construction efficiency.

[0021] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise one" do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0022] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart construction site construction safety and quality detection method based on big data, characterized by: The method comprises the following steps: Step 1: Install monitoring and sensors. Place multiple sensors and cameras at the construction site to monitor the environmental conditions, equipment status and worker activities at the construction site in real time. Step 2: Intelligent analysis, which uses machine learning algorithms to analyze the collected data to identify potential safety risks and quality issues; Step 3: Predictive maintenance, using big data to predict equipment failures and maintenance needs, reduce unexpected downtime, and improve construction efficiency; Step 4: Risk assessment: conduct real-time assessment of the risks of high-altitude operations or electrical safety risk factors at the construction site, issue early warnings in a timely manner, and take preventive measures; Step 5: Quality control, using image recognition and data analysis technology through the quality inspection system to automatically detect the concrete strength and steel layout construction quality to ensure compliance with standards; Step 6: Safety management: Worker identity verification through fingerprint or facial recognition technology to ensure that only authorized personnel enter the construction site area, and then use smart wearable devices to ensure that workers wear and use safety equipment correctly; Step 7: Accident prevention, by analyzing workers’ dangerous behaviors and on-site safety conditions, predicting possible accidents and taking measures to avoid them; Step 8: Remote real-time management: project managers and safety managers can remotely view the surveillance video of the camera through the cloud platform and manage the construction site in real time; Step 9: Decision support, providing big data-driven decision support to help management develop more effective construction plans and safety strategies; Step 10: Intelligent reporting: the system automatically generates construction progress and safety and quality reports for easy review and recording; Step 11: Interface display: the text and pictures implemented by the above steps are displayed through a mobile APP or a display screen, so that all users can quickly access and view the required information.

2. The method for detecting safety and quality of intelligent construction sites based on big data according to claim 1 is characterized in that: It also includes the use of virtual reality and augmented reality technologies to provide safety education and skills training for workers, simulate potential dangerous situations and emergency responses, and allow workers to practice different ways of dealing with different dangerous situations, while allowing multiple users to participate in training at the same time for team collaboration and communication.

3. The method for detecting safety and quality of intelligent construction sites based on big data according to claim 1 is characterized in that: The environmental conditions in step 1 collect temperature, humidity, noise, vibration and air quality data, as well as construction progress and quality indicators through various sensors. The equipment status specifically refers to the vibration, pressure and current of the equipment to facilitate the subsequent prediction of equipment failure. The worker activities specifically use video analysis software to detect whether the workers are working in dangerous areas.

4. The method for detecting safety and quality of intelligent construction sites based on big data according to claim 1 is characterized in that: The step 5 also includes using 3D laser scanning technology to obtain accurate three-dimensional data of the construction area, comparing it with the design model, detecting construction deviations, integrating and comparing the design data with the actual construction situation through BIM technology, realizing visualization and quality control of the construction process, and using RFID tags to track building materials and components to ensure the correctness and traceability of material use.

5. The method for detecting safety and quality of intelligent construction sites based on big data according to claim 1 is characterized in that: It also includes integrating various hardware devices, software applications and data platforms in each step into a unified system to achieve data sharing and functional collaboration for better management.

6. Intelligent construction site safety and quality inspection system based on big data, characterized by: It includes video surveillance module, sensor network module, behavior recognition module, worker safety module, geographic information module, Internet of Things platform, predictive analysis module, accident reporting and tracking module, mobile application and alarm module, risk assessment module, cloud platform and emergency response module; The video monitoring module monitors the construction site in real time through cameras installed at key locations; The sensor network module monitors the status of construction equipment by deploying environmental sensors on the construction site to monitor environmental parameters and installing equipment sensors on the construction site equipment; The behavior recognition module is used to train the model to identify improper operations or specific illegal behaviors of workers; The worker safety module is used for health monitoring components and location tracking components worn on workers; The geographic information module is used to analyze the spatial distribution of workers and equipment using GIS software and optimize the construction layout; The IoT platform is used to integrate data from various devices and sensors into the IoT platform, and then use the analysis tools and other modules of the IoT platform itself to make data-driven decisions; The predictive analysis module predicts potential safety risks by analyzing historical data and real-time data, and identifies trends in safety and quality issues, taking measures in advance to perform trend analysis; The accident reporting and tracking module allows workers and managers to report accidents through mobile devices or web pages, and the system automatically records and analyzes accident reports to find out the specific causes; The mobile application and alarm module allows managers and workers to communicate in real time through the mobile application. When a dangerous situation is detected, the system can send an emergency alarm through the mobile application; The risk assessment module uses a mobile device or web page to conduct daily safety checks and also uses software tools to assess the risk level of specific operations; The cloud platform is used to store all monitoring and analysis data in the cloud, ensuring data security and accessibility, and enabling managers to remotely access the monitoring system through any device; The emergency response module formulates detailed emergency plans for different situations and integrates them into the system. When an accident occurs, the system automatically activates the corresponding emergency plan to guide on-site personnel to handle the emergency.

7. The intelligent construction site construction safety and quality detection system based on big data according to claim 6 is characterized by: The behavior recognition module also includes using video analysis software to detect whether workers are wearing safety equipment or working in a dangerous area.

8. The intelligent construction site construction safety and quality detection system based on big data according to claim 6 is characterized by: The worker safety module also includes a smart hard hat with built-in sensors to detect impacts and record accident data, as well as environmental monitoring capabilities for impact detection and monitoring of the worker's surrounding environmental conditions.

9. The intelligent construction site construction safety and quality detection system based on big data according to claim 6 is characterized by: It also includes a personnel entry and exit monitoring module. Through near-field communication technology, NFC tags are set at the entrance and key areas of the construction site, and workers sign in and locate through NFC devices.

10. The intelligent construction site construction safety and quality detection system based on big data according to claim 6 is characterized by: It also includes VR and AR training modules, devices for immersive experience or overlaying real-life vision through head-mounted displays and smart glasses, and software for developing and running VR and AR applications that simulate construction environments and safety training scenarios. It uses 3D modeling software to create three-dimensional models of construction sites, equipment and processes, conduct safety education, skills training, construction simulation and on-site navigation, improve workers' safety awareness and operational skills, and optimize construction processes and project management.

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